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Palmprint Feature Extraction Method Based on Rotation-invariance

机译:基于旋转不变性的PalmPrint特征提取方法

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Feature extraction is one of most basic problems in the research of palmprint recognition. Extracting effective palmprint feature is the crucial problem in the field of palmprint recognition. There was a research focus on how to select the feature. The lacking of main orientation for palmprint recognition system will lead to an incorrect feature extraction and matching. In order to extract more precise palmprint feature, a new method for feature extraction of palmprint was proposed in the research of palmprint recognition, which could improve the efficiency of identification. Firstly, calculating the main orientation of the whole image, and then adjusting the gradient of each pixel according to the main orientation to ensure this method has rotation invariance. Secondly, combining with the method of histogram of oriented gradient and dominant orientation. Finally, the feature value of palmprint was obtained. A reasonable threshold is set to estimate the similarity between the experimental images and the sample images. The experimental results showed that the method proposed in this paper can improve the efficiency of identification.
机译:特征提取是掌上识别研究中最基本的问题之一。提取有效的掌纹特征是Palmprint识别领域的关键问题。有一个研究侧重于如何选择该功能。缺乏Palmpret识别系统的主要方向将导致不正确的特性提取和匹配。为了提取更多精确的掌纹特征,提出了一种新的掌纹特征提取方法,在掌上识别的研究中提出了一种可以提高鉴定效率。首先,计算整个图像的主定向,然后根据主定向调整每个像素的梯度,以确保该方法具有旋转不变性。其次,与定向梯度和主导取向的直方图的方法组合。最后,获得了PalmPrint的特征值。将合理的阈值设置为估计实验图像和样本图像之间的相似性。实验结果表明,本文提出的方法可以提高鉴定效率。

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